Artificial intelligence (AI) is a branch of science and engineering that focuses on the computational understanding of intelligent behavior. Many human professions, including clinical diagnosis and prognosis, are greatly useful from AI. Antimicrobial resistance (AMR) is among the most critical challenges facing Pakistan and the rest of the world. The rising incidence of AMR has become a significant issue, and authorities must take measures to combat the overuse and incorrect use of antibiotics in order to combat rising resistance rates. The widespread use of antibiotics in clinical practice has not only resulted in drug resistance but has also increased the threat of super-resistant bacteria emergence. As AMR rises, clinicians find it more difficult to treat many bacterial infections in a timely manner, and therapy becomes prohibitively costly for patients. To combat the rise in AMR rates, it is critical to implement an institutional antibiotic stewardship program that monitors correct antibiotic use, controls antibiotics, and generates antibiograms. Furthermore, these types of tools may aid in the treatment of patients in the event of a medical emergency in which a physician is unable to wait for bacterial culture results. AI’s applications in healthcare might be unlimited, reducing the time it takes to discover new antimicrobial drugs, improving diagnostic and treatment accuracy, and lowering expenses at the same time. The majority of suggested AI solutions for AMR are meant to supplement rather than replace a doctor’s prescription or opinion, but rather to serve as a valuable tool for making their work easier. When it comes to infectious diseases, AI has the potential to be a game-changer in the battle against antibiotic resistance. Finally, when selecting antibiotic therapy for infections, data from local antibiotic stewardship programs are critical to ensuring that these bacteria are treated quickly and effectively. Furthermore, organizations such as the World Health Organization (WHO) have underlined the necessity of selecting the appropriate antibiotic and treating for the shortest time feasible to minimize the spread of resistant and invasive resistant bacterial strains.

The important role of Lactiplantibacillus plantarum strains in improving the human mucosal and systemic immunity, preventing non-steroidal anti-provocative drug-induced reduction in T-regulatory cells, and as probiotic starter cultures in food processing has motivated in-depth molecular and genomic research of these strains. The current study, building on this research concept, reveals the importance of Lactiplantibacillus plantarum 13-3 as a potential probiotic and bacteriocin-producing strain that helps in improving the condition of the human digestive system and thus enhances the immunity of the living beings via various extracellular proteins and exopolysaccharides. We have assessed the stability and quality of the L. plantarum 13-3 genome through de novo assembly and annotation through FAST-QC and RAST, respectively. The probiotic-producing components, secondary metabolites, phage prediction sites, pathogenicity and carbohydrate-producing enzymes in the genome of L. plantarum 13-3 have also been analyzed computationally. This study reveals that L. plantarum 13-3 is nonpathogenic with 218 subsystems and 32,918 qualities and five classes of sugars with several important functions. Two phage hit sites have been identified in the strain. Cyclic lactone autoinducer, terpenes, T3PKS, and RiPP-like gene clusters have also been identified in the strain evidencing its role in food processing. Combined, the non-pathogenicity and the food-processing ability of this strain have rendered this strain industrially important. The subsystem and qualities characterization provides a starting point to investigate the strain’s healthcare-related applications as well.

Mucormycosis is a group of infections, caused by multiple fungal species, which affect many human organs and is lethal in immunocompromised patients. During the COVID-19 pandemic, the current wave of mucormycosis is a challenge to medical professionals as its effects are multiplied because of the severity of COVID-19 infection. The variant of concern, Omicron, has been linked to fatal mucormycosis infections in the US and Asia. Consequently, current postdiagnostic treatments of mucormycosis have been rendered unsatisfactory. In this hour of need, a preinfection cure is needed that may prevent lethal infections in immunocompromised individuals. This study proposes a potential vaccine construct targeting mucor and rhizopus species responsible for mucormycosis infections, providing immunoprotection to immunocompromised patients. The vaccine construct, with an antigenicity score of 0.75 covering, on average, 92–98% of the world population, was designed using an immunoinformatics approach. Molecular interactions with major histocompatibility complex-1 (MHC-I), Toll-like receptors-2 (TLR2), and glucose-regulated protein 78 (GRP78), with scores of −896.0, −948.4, and −925.0, respectively, demonstrated its potential to bind with the human immune receptors. It elicited a strong predicted innate and adaptive immune response in the form of helper T (Th) cells, cytotoxic T (TC) cells, B cells, natural killer (NK) cells, and macrophages. The vaccine cloned in the pBR322 vector showed positive amplification, further solidifying its stability and potential. The proposed construct holds a promising approach as the first step towards an antimucormycosis vaccine and may contribute to minimizing postdiagnostic burdens and failures.

All nutrient-rich feed and food environments, as well as animal and human mucosae, include lactic acid bacteria known as Lactobacillus plantarum. This study reveals an advanced analysis to study the interaction of probiotics with the gastrointestinal environment, irritable bowel disease, and immune responses along with the analysis of the secondary metabolites’ characteristics of Lp YW11. Whole genome sequencing of Lp YW11 revealed 2297 genes and 1078 functional categories of which 223 relate to carbohydrate metabolism, 21 against stress response, and the remaining 834 are involved in different cellular and metabolic pathways. Moreover, it was found that Lp YW11 consists of carbohydrate-active enzymes, which mainly contribute to 37 glycoside hydrolase and 28 glycosyltransferase enzyme coding genes. The probiotics obtained from the BACTIBASE database (streptin and Ruminococcin-A bacteriocins) were docked with virulent proteins (cdt, spvB, stxB, and ymt) of Salmonella, Shigella, Campylobacter, and Yersinia, respectively. These bacteria are the main pathogenic gut microbes that play a key role in causing various gastrointestinal diseases. The molecular docking, dynamics, and immune simulation analysis in this study predicted streptin and Ruminococcin-A as potent nutritive bacteriocins against gut symbiotic pathogens.

The foremost wastage of bakery products which mainly disturbs the food supply chain, especially in remote areas, is fungal growth. Good quality bread, especially with good height and volume, is the demand of every customer. Here, we aimed to develop a unique antimicrobial approach for the enhancement of the quality aspects and longevity of bread, using the synthesis of hydrogen peroxide in bread, the glucose oxidase (GOx) bioactivity, and oxidation of thiol protein bonds, which greatly enhance dough rheology, volume, and height by providing structural stability to the bread. An Aspergillus niger-purified enzyme was immobilized on zinc oxide nanoparticles (ZnONPs) and afterwards immersed in a buffered solution to create a mixture of GOx/ZnONPs. Analyses conducted after localization revealed that the immobilized enzyme was more active than the mobilized enzyme. GOx/ZnONPs were employed in the mixing process of bread production. The treated and control groups were evaluated for dough rheology and quality metrics including bread height and volume and storage at ambient temperature and conditions to determine shelf life by demonstrating fungal growth. In addition, antimicrobial activity was evaluated by measuring the microbiological load in terms of colony-forming units. Contrary to the control, the use of GOx/ZnONPs significantly improved bread quality, particularly bread height by 34.4%, crumb color, and volume by 30%. The shelf life of bread treated with GOx/ZnONPs was greatly extended, and the microbiological load, including yeast and mold, and total bacterial count were much lower in the GOx/ZnONPs treatment group than in the control group.

Human Parainfluenza Virus (HPIV) Type-1, which is an anti-sense ribonucleic acid (RNA) virus belonging to the paramyxoviridae family, induces upper and lower respiratory tract infections. The infections caused by the HPIV Type-1 virus are usually confined to northwestern regions of America. HPIV-1 causes infections through the virulence of the hemagglutinin-neuraminidase (HN) protein, which plays a key role in the attachment of the viral particle with the host’s receptor cells. To the best of our knowledge, there is no effective antiviral drugs or vaccines being developed to combat the infection caused by HPIV-1. In the current study, a multiple epitope-based vaccine was designed against HPIV-1 by taking the viral HN protein as a probable vaccine candidate. The multiple epitopes were selected in accordance with their allergenicity, antigenicity and toxicity scoring. The determined epitopes of the HN protein were connected simultaneously using specific conjugates along with an adjuvant to construct the subunit vaccine, with an antigenicity score of 0.6406. The constructed vaccine model was docked with various Toll-like Receptors (TLRs) and was computationally cloned in a pET28a (+) vector to analyze the expression of vaccine sequence in the biological system. Immune stimulations carried out by the C-ImmSim Server showed an excellent result of the body’s defense system against the constructed vaccine model. The AllerTop tool predicted that the construct was non-allergen with and without the adjuvant sequence, and the VaxiJen 2.0 with 0.4 threshold predicted that the construct was antigenic, while the Toxinpred predicted that the construct was non-toxic. Protparam results showed that the selected protein was stable with 36.48 instability index (II) scores. The Grand average of Hydropathicity or GRAVY score indicated that the constructed protein was hydrophilic in nature. Aliphatic index values (93.53) confirmed that the construct was thermostable. This integrated computational approach shows that the constructed vaccine model has a potential to combat laryngotracheobronchitis infections caused by HPIV-I.